The techniques of cellular biology have been applied to numerous fields of scientific inquiry. A cell-line-based biological experiment on specific biological markers is typically a process that groups a set of assay plates into a collection designed to achieve a scientific purpose, or is a composite of several such processes. One known technique in cytobiological research involves the analysis of cellular images from such experiments.
Experiments typically combine sets of assay plates to achieve some scientific purpose. An assay plate is a collection of wells arranged in groups of wells. A well group is a set of wells on an assay plate, or ranging across two or more assay plates, that represents a specific collection of wells for distinct analysis.
A treatment is a particular drug or other external stimulus (or a combination of stimuli, drugs, or drugs+stimulus/stimuli) to which wells are exposed on an assay plate. Every plate typically contains multiple sets of wells that constitute treatment well groups. A treatment plate is a plate containing an array of treatment compounds in well groups. Each well group may contain one or more treatment compounds in each well (the treatment). Each treatment well in a group contains a specific dilution (or dose) of the group treatment. Typically assay plate wells get a specific amount of compound from the corresponding well on the treatment plate.
A well image is one of several possible images of a single well and is the smallest unit of analysis in the system. Well images relate to specific cell markers and are at specific sites in the well. Typically cells of a specified type are introduced into each of the wells of the assay plate by a process sometimes referred to as plating. (Note that a given well may include cells of different types, specifically selected for a particular experiment.) A certain amount of a reagent medium is added to each well to promote cell growth. A certain amount of a treatment is added to each well, combining with the cells and media already present. One or more reagents may comprise a treatment. After the treatment has acted upon the cells in the several wells of the assay plate for the time specified by the experimenter, the cells are typically washed, fixed, and stained. An experiment may contain groups of plates fixed at different times (time points). Images, typically photomicroscopic images, are taken for the cells in the several wells of the assay plate or plates. Finally, an experimenter analyzes these images to determine the effect of the treatment.
Each of these steps is exacting, repetitive, and many of them require significant amounts of time from highly trained experimenters to complete. A thorough analysis of the effects of one treatment on one cell line may require tens or even hundreds of wells. This is multiplied where the treatment is analyzed against multiple cell lines, or where a cell line is used to determine the effects of multiple treatments.
What is needed is a methodology which provides tools that allow a designer to design an experiment that combines cell lines, marker sets, time points, and treatment plates. These tools should permit the full specification of the experimental process through a process model that generates a process, or collection of tasks. The system should provide the designer with the ability to specify the structure of the experimental process. The system should then specify the processes and tasks for each experiment, automating the process where possible.
The system should enable a user to plan for and maintain adequate experimental infrastructure for planned experiments. By way of illustration, this infrastructure includes, but is not limited to hardware, software, reagents, treatments, and maintenance processes. The system should track the infrastructure of experiments by tracking the individual hardware systems, software systems, reagents, treatments, and maintenance processes required to conduct the experiment. The system should provide reports as planning tools for users to help them to keep adequate supplies and systems on hand and in good repair.
Automated milestones, for instance barcode scanning, task completion updates, and so forth, should be implemented to provide tracking capabilities that give designers, supervisors, and experimenters the ability to obtain experiment status and to intervene in the process where required, preferably through remote interfaces.
The system should provide a full range of tools for validating experimental results. The system should validate experimental results by storing the results of the experiment and by enabling feedback from scientific analysis of the results. Experimental result validation consists of internal consistency of the results and reproducibility of the results. These consistency and reproducibility metrics provide means for designers and experimenters to identify result failures in images, wells, and plates. By way of illustration, but not limitation, consistency metrics may include cell distribution, focus/exposure tests, contamination tests, and control measure consistency with respect to benchmarks. Examples of reproducibility metrics include variance or standard deviation or coefficient of variation of consistency metrics.
The system should provide failure and defect tracking tools to track experimental defects and the failures they cause.
To create a system for validating experimental processes the system should assist in validating experimental processes by storing the processes and tasks undertaken as part of the experiment. These process and task objects provide a complete history of the experiment with all significant milestones recorded with their date and time together with their process models, reusable protocols for generating the process for each experiment. The failure and defect tracking systems track defects and failures in the processes and tasks reported by the system and its users, both of which are sometimes referred to generically hereinafter as “actors”.
The system should be capable of creating reusable information, or feedback, about systems failures that is useful for improving the system. Users could thus use this system to improve the visibility of failures within the organization and to improve communication with respect to failures.
The system should be capable of creating reusable information about opportunities to improve the system. Users could thus also use this system to improve the visibility and communication of progress in realizing opportunities within the organization. The system should provide for creating reusable information, or feedback about specific instances of the system that lets users make comments on operational systems. It should further enable management to plan improvement work based on prioritization of the comments.
The system should enable users, applications, and database servers to report and track system defects, and to provide management the ability to plan improvement work based on prioritization of defect fixing and to understand the current situation with respect to the life cycle of defects in the overall system. Managers can also use this information to improve the visibility of defects within the organization and to improve communication with respect to defects.
Optimally, the system should present a flexible, fully automated system for applying image and data analysis algorithms to input images that optimizes image and analysis throughput. The system should permit easy modification of the algorithm structure and easy control of runtime processing. Developers should be able to add new analytical transactions to the system quickly and easily, and operators should be able to control and prioritize analysis jobs using the running system.